---
type: claim
domain: ai-alignment
description: "Alexander's taxonomy of four mechanisms that prevent multipolar traps from destroying all value — excess resources, physical limitations, utility maximization, and coordination — provides a framework for understanding which defenses AI undermines and which remain viable"
confidence: likely
source: "Scott Alexander 'Meditations on Moloch' (slatestarcodex.com, July 2014), Schmachtenberger metacrisis framework, Abdalla manuscript price-of-anarchy analysis"
created: 2026-04-02
depends_on:
- AI accelerates existing Molochian dynamics by removing bottlenecks not creating new misalignment because the competitive equilibrium was always catastrophic and friction was the only thing preventing convergence
- technology advances exponentially but coordination mechanisms evolve linearly creating a widening gap
related:
- multipolar traps are the thermodynamic default because competition requires no infrastructure while coordination requires trust enforcement and shared information all of which are expensive and fragile
- indigenous restraint technologies like the Sabbath are historical precedents for binding the maximum power principle through social technology
reweave_edges:
- multipolar traps are the thermodynamic default because competition requires no infrastructure while coordination requires trust enforcement and shared information all of which are expensive and fragile|related|2026-04-04
- indigenous restraint technologies like the Sabbath are historical precedents for binding the maximum power principle through social technology|related|2026-04-18
sourced_from:
- inbox/archive/2014-07-30-scott-alexander-meditations-on-moloch.md
---

# four restraints prevent competitive dynamics from reaching catastrophic equilibrium and AI specifically erodes physical limitations and bounded rationality leaving only coordination as defense

Scott Alexander's "Meditations on Moloch" identifies four categories of mechanism that prevent competitive dynamics from destroying all human value. Understanding which restraints AI erodes and which it leaves intact determines where governance investment should concentrate.

**The four restraints:**

1. **Excess resources** — When carrying capacity exceeds population, non-optimal behavior is affordable. A species with surplus food can afford altruism. A company with surplus capital can afford safety investment. This restraint erodes naturally as competition fills available niches — it is the first to fail and the least reliable.

2. **Physical limitations** — Biological and material constraints prevent complete optimization. Humans need sleep, can only be in one place, have limited information-processing bandwidth. Physical infrastructure has lead times measured in years. These constraints set a floor below which competitive dynamics cannot push — organisms cannot evolve arbitrary metabolisms, factories cannot produce arbitrary quantities, surveillance requires human intelligence officers (the Stasi needed 1 agent per 63 citizens).

3. **Utility maximization / bounded rationality** — Competition for customers partially aligns producer incentives with consumer welfare. But this only works when consumers can evaluate quality, switch costs are low, and information is symmetric. Bounded rationality means actors cannot fully optimize, which paradoxically limits how destructive their competition becomes.

4. **Coordination mechanisms** — Governments, social codes, professional norms, treaties, and institutions override individual incentive structures. This is the only restraint that is architecturally robust — it doesn't depend on abundance, physical limits, or cognitive limits, but on the design of the coordination infrastructure itself.

**AI's specific effect on each restraint:**

- **Excess resources (#1):** AI increases resource efficiency, which can either extend surplus (if gains are distributed) or eliminate it faster (if competitive dynamics capture gains). Direction is ambiguous — this restraint was already the weakest.

- **Physical limitations (#2):** AI fundamentally erodes this. Automated systems don't fatigue. AI surveillance scales to marginal cost approaching zero (vs the Stasi's labor-intensive model). AI-accelerated R&D compresses infrastructure lead times. The manuscript's FERC analysis — 9 substations could take down the US grid — illustrates how physical infrastructure was already fragile; AI-enabled optimization of attack vectors makes it more so.

- **Bounded rationality (#3):** AI erodes this from both sides. It enables competitive optimization at speeds that bypass human deliberation (algorithmic trading, automated content generation, AI-assisted strategic planning). But it also potentially improves decision quality through better information processing. Net effect on competition is likely negative — faster optimization in competitive contexts outpaces improved cooperation.

- **Coordination mechanisms (#4):** AI has mixed effects. It can strengthen coordination (better information aggregation, lower transaction costs, prediction markets) or undermine it (deepfakes eroding epistemic commons, AI-powered regulatory arbitrage, surveillance enabling authoritarian lock-in). This is the only restraint whose trajectory is designable rather than predetermined.

**The strategic implication:** If restraints #1-3 are eroding and #4 is the only one with designable trajectory, then the alignment problem is fundamentally a coordination design problem. Investment in coordination infrastructure (futarchy, collective intelligence architectures, binding international agreements) is more important than investment in making individual AI systems safe — because individual safety is itself subject to the competitive dynamics that coordination must constrain.

This connects directly to the existing KB claim that [[technology advances exponentially but coordination mechanisms evolve linearly creating a widening gap]]. The four-restraint framework explains *why* that gap matters: technology erodes three of four defenses, and the fourth — coordination — is evolving too slowly to compensate.

## Challenges

- Alexander's taxonomy is analytical, not empirical. The four categories may not be exhaustive — social/cultural norms, for instance, may constitute a distinct restraint mechanism that doesn't reduce neatly to "coordination."
- The claim that AI specifically erodes #2 and #3 while leaving #4 designable may be too optimistic about #4. If AI-powered disinformation erodes the epistemic commons required for coordination, then #4 is also under attack, not just designable.
- "Leaving only coordination as defense" is a strong claim. Physical limitations still constrain AI deployment substantially (compute costs, energy requirements, chip supply chains). The governance window may be narrow but it exists.

---

Relevant Notes:
- [[AI accelerates existing Molochian dynamics by removing bottlenecks not creating new misalignment because the competitive equilibrium was always catastrophic and friction was the only thing preventing convergence]] — the parent mechanism this taxonomy structures
- [[technology advances exponentially but coordination mechanisms evolve linearly creating a widening gap]] — the linear coordination evolution is specifically about restraint #4
- [[AI alignment is a coordination problem not a technical problem]] — this taxonomy explains why: restraints #1-3 are eroding, #4 is the designable one
- [[physical infrastructure constraints on AI development create a natural governance window of 2 to 10 years because hardware bottlenecks are not software-solvable]] — a specific instance of restraint #2 that is degrading

Topics:
- [[_map]]